Follow blockchain research across journals, conferences, and preprint repositories.
8,484 results · page 53 of 354
Abhraneel Dutta, Veronika Kuchta, Francesco Sica
No abstract is available for this record.
Jun Gorai
No abstract is available for this record.
Lee Reiners
No abstract is available for this record.
Zhao Zhang, Chunxiang Xu, Chuhan Ma
Communication protocol is a fundamental component of modern networking. With proliferation of networking and communication, users have become more concerned about privacy. This leads to development of end-to-end encrypted messaging systems which provides confidential communication. Besides confidentiality, there is an increasing demand for additional security properties such as unforgeability, anonymity, off-the-record (OTR), and consistency. However, efficiently achieving these properties simultaneously, especially on resource-constrained mobile devices, remains a significant challenge. In this paper, we propose MERIT, a novel multi-designated receiver authenticated broadcast encryption scheme that satisfies all the above security guarantees in a highly efficient manner. MERIT ensures the following key properties: (i) unforgeability prevents unauthorized parties from generating valid messages; (ii) privacy safeguards the messages and identities of the sender and receivers from non-designated parties; (iii) OTR ensures that receivers cannot later prove the origin of the messages even with their secret keys; and (iv) consistency ensures that all designated receivers obtain identical decrypted messages and identities. The core building block of MERIT is a practical multi-designated verifier signature (PMDVS), which might be of independent interest. We employed a novel batched cut-and-choose technology to prove that the ciphertext is well-formed. This results in an order-of-magnitude efficiency improvement in our scheme compared to its counterparts that rely on general-purpose zero-knowledge proofs. We then show how MERIT leverages PMDVS to provide unforgeability, privacy, OTR, and consistency in the scenario of group messaging. We provide security analysis to demonstrate that MERIT satisfies these security guarantees. We also conduct a thorough performance implementation, and the experimental results demonstrate that MERIT is highly efficient for deployment on mobile devices.
S. Usharani, P. Manju Bala, A. Devi, A. Balachandar · 5 authors
No abstract is available for this record.
Benjamin Nweke, Gholamreza Ramezan, Soheil Saraji
No abstract is available for this record.
Masoomeh Bahrami, Doyeop Lee, Namgyun Kim, JeeHee Lee
No abstract is available for this record.
William D. Diacont
We present Processual Memory Architecture (PMA), a computational framework that unifies data storage and computation by representing all information as transformation functions rather than static state, rendering the traditional ontological distinction between them architecturally unnecessary. In PMA, storing information means encoding it as a mathematical transformation that produces the data when applied to a standardized canonical input; reading means applying the transformation; and computing means composing transformations. This inversion of the conventional von Neumann paradigm yields five emergent architectural properties—structural auditability, transparent reasoning, enforced constraints, tamper evidence, and reversibility—that collectively enable verifiable computation: systems that can mathematically verify the integrity and correctness of their own reasoning chains. We provide a complete mathematical specification of PMA over Galois fields GF(2k) with roundtrip exactness guarantees, constructive algorithms for both invertible and non-invertible encoding modes, and a reference permutation-based embodiment with explicit bit-level storage formats. We analyze thermodynamic properties under reversible logic implementation, demonstrating that PMA operations on adiabatic substrates can approach within 10× of the Landauer limit at the localnode level. We then present the integration architecture for PMA with artificial general intelligence (AGI) safety frameworks, showing how transformation-based reasoning enables safety constraints that are structural rather than advisory—creating systems where unsafe behavior is computationally undefined rather than merely prohibited. We discuss applications to financial auditing, medical AI verification, and autonomous systems governance, and compare PMA's approach to verifiable computation with existing paradigms including blockchain, zero-knowledge proofs, and mechanistic interpretability.
Hani Al-Balasmeh
No abstract is available for this record.
Mojtaba Khalili
Quasi-adaptive non-interactive zero-knowledge (QA-NIZK) arguments are fundamental cryptographic primitives widely used in privacy-preserving technologies such as anonymous credentials, group signatures, e-cash, and blockchain-based applications. We present the first tightly secure unbounded simulation sound quasi-adaptive non-interactive zero-knowledge argument system from simple assumptions. The construction has a security loss ofO(1), a compact common reference string, constant size proofs, and its security relies on the hardness of the well-known SXDH assumption. Our result improves state-of-the-art (Couteau and Hartmann, CRYPTO 2020) in terms of the proof size (about three times), a lower security loss, and also with respect to the underlying hardness assumptions. The tight security reduction enables shorter key-length recommendations, leading to improved concrete efficiency. Our main technical contribution is a novel proof technique inspired by the randomization technique of the Naor-Yung double-encryption paradigm and the adaptive partitioning due to Hofheinz (EUROCRYPT 2017).
CS Chai
No abstract is available for this record.
Dikshant Agarwal
No abstract is available for this record.
Ali Şah Özcan, Cihangir Tezcan, Erkay Savaş
No abstract is available for this record.
Lanyi Wang
In recent years, decentralized networks have increasingly relied on secure and efficient data exchange systems to support large-scale operations and collaborative processes. Traditional centralized systems face challenges in scalability, transparency, and trust management, which blockchain technology can address. However, existing research has primarily focused on data integrity and static trust models, neglecting dynamic trust propagation, privacy concerns, and the interpretability of trust-related decisions. This study proposes a blockchain-driven information system that integrates a Trust Score Aggregation Module (TSAM), a Hybrid Consensus Protocol (HCP), and a Privacy-Preserving Smart Contract Framework (PPSCF) to address these gaps. The TSAM enables dynamic trust propagation, while the HCP optimizes communication efficiency, and the PPSCF ensures privacy through zero-knowledge proofs. Experimental results show that the proposed system reduces latency by 27.3 % (0.98±0.07 s), increases throughput by 27.1 % (140±6 tps), and achieves a 33.3 % reduction in trust variance compared to baseline systems. The system also improves interpretability by 22.0 %, maintaining low privacy overhead (5.1±0.8 %). This research advances the understanding of blockchain-based trust management in decentralized environments, providing a scalable, interpretable, and privacy-preserving framework that can be applied across various domains and operational scales. The proposed methodology lays a foundation for future blockchain applications in large-scale systems, particularly in environments requiring robust data governance and compliance.
Quoc Khanh Huynh, Nhat Nguyen Nguyen, Tuan-Dung Tran
No abstract is available for this record.
M. Sreelakshmi, Shaik Naseera
No abstract is available for this record.
Zhiqiang Zhang, Youwen Zhu, Xiaodong Yang, Xiaohui Ding · 7 authors
Attribute-Based Encryption (ABE) enables fine-grained access control over outsourced data, but its key generation process typically requires users to disclose their complete attribute sets, introducing significant privacy risks. Existing privacy-preserving approaches—such as those based on zero-knowledge proofs or tightly coupled interactive protocols—suffer from limited scalability, high communication costs, and insufficient support for selective attribute disclosure. To address these limitations, we propose a privacy-enhancing key generation protocol guided by the principle ofMinimal Disclosure, which ensures that users disclose only the minimally necessary subset of attributes required for authorization. Our protocol decouples attribute verification from key issuance: users first obtain cryptographically verifiable attribute tokens, and later issue blinded key requests over selectively chosen attributes. This design enables selective disclosure, supports reusable attribute credentials, and enhances user autonomy. To improve scalability, we introduce a lightweight batch verification mechanism that reduces computation and communication overhead for the attribute authority. We prove that our protocol achieves thebindingandhidingproperties under standard cryptographic assumptions, and we formally verify these guarantees in the symbolic model using the ProVerif tool. In addition, we propose two privacy metrics—AttributeInference Gain (AIG) andPrivacy Gain (PG)—alongside an entropy-based analysis to quantify resistance against attribute inference attacks. Experimental results show that our scheme effectively mitigates inference leakage while offering substantial efficiency gains compared to existing schemes.
Filippo Caprioglio
No abstract is available for this record.
Rajesh Bose, Shrabani Sutradhar, Arfat Ahmad Khan, Sandip Roy · 7 authors
ABSTRACT The promise of blockchain applications is transformative in terms of certificate verification and managing digital identities in the various fields, such as education, healthcare and land records. Nevertheless, current blockchain‐based certificate solutions have serious shortcomings: most are based on simple cryptography protection with no privacy‐preserving systems, have low throughput (16.67 TPS in typical Ethereum‐based systems), have unpredictable response times under varying loads, are not standardised across industries and are expensive to operate due to gas fees. Besides, the current implementations are mostly either theoretical or without performance tests in practice. This paper fills these gaps by suggesting a Plonk‐based system that incorporates zero‐knowledge proofs, digital signatures and trusted identity verification to improve the efficiency, security, and privacy of the verifiable credential digital identity verification and management systems (VC DIVMS). It was implemented at JIS University, India, with 50 transactions per minute (an improvement of 200% over Ethereum), an error rate of 244–1277ms in response times under load conditions (24‐33 faster than Ethereum) and high‐level privacy through ZKP. Contrary to currently used models that are sector‐specific, the offered Plonk framework offers a single, scalable, privacy‐focused model that can be applied in areas of education, healthcare, or credit verification. Intense testing ensured both resilience, scalability and compatibility with a demanding environment, making Plonk a strong and secure substitute to decentralised identity verification and credential management that is resistant to tampering.
Henry Zhu
This thesis advances privacy-preserving solutions essential for addressing contemporary technological challenges in smart cities, decentralized systems, and algorithmic decision-making processes. Firstly, we introduce a hybrid sensing framework integrating Internet of Things (IoT) sensors and crowdsensing techniques to overcome limitations inherent in traditional methods. The hybrid sensing model incentivizes voluntary user contributions to complement fixed-location IoT sensors, ensuring reliable and comprehensive data collection while maintaining user anonymity through a privacy-preserving protocol. We implement this model in a smart parking application, demonstrating significant improvements in data accuracy and user engagement. Secondly, we propose a decentralized anonymous crowdsourcing system leveraging blockchain technology, which removes reliance on centralized intermediaries, thereby enhancing transparency and mitigating biases. Our system integrates anonymous payments using the Zerocoin protocol framework, eliminating the need for worker identity registration and trusted setups, thus fostering genuinely anonymous participation. Empirical analyses confirm that our approach maintains practical efficiency in transaction verification and moderate blockchain gas costs. Lastly, we tackle fairness and transparency in algorithmic decision-making processes, addressing public concerns regarding inherent biases and opaque computational practices. We develop a privacy-preserving, publicly verifiable framework that combines succinct zero-knowledge proofs with blockchain infrastructure, allowing independent verification of algorithmic fairness without exposing sensitive inputs or decision-making algorithms. Our concrete instantiation employs a restricted KZG polynomial commitment scheme alongside the Sonic zk-SNARK protocol, demonstrating small proof sizes, efficient verification, and practical deployment feasibility. Collectively, this thesis contributes significantly to the field by providing robust, scalable, and privacy-conscious technologies tailored for contemporary smart city applications and decentralized computational ecosystems.
Rubén Armañanzas
No abstract is available for this record.
Mohammad Rafiqul Islam, Silicon-Saffat TRISDUCTION
The P versus NP problem, formalized by Cook (1971) and designated a Clay Millennium Prize Problem in 2000, asks whether every computational problem whose solution can be verified in polynomial time can also be solved in polynomial time. For fifty-five years the problem has resisted all single-axis formal resolution attempts. Three independently proven barrier results have demonstrated that all currently known classes of mathematical proof technique are structurally incapable of settling the question within the formal axis alone. This paper presents a unified geometric determination of both P = NP and P ≠ NP using the Trisduction ENGINE, an epistemic certification architecture operating across three orthogonal warrant-vectors: Formal (V_F), Empirical (V_E), and Phenomenological (V_P). Version 10.0 introduces two architectural upgrades over prior versions: Rule 9 Axiomatic Quarantine, which formally removes the Turing Machine abstraction from the framework's admissible baseline and replaces it with the Tri-Layer Plenum topology; and the Meta-Epistemic Hierarchy (Geometry > Mathematics > Logic), which resolves the recurring drift pattern in which formal demands were treated as epistemically superior to geometric physical measurement. The two audits are presented as a single master document to make the asymmetry between the claims structurally transparent: P = NP carries zero positive warrant across all three axes and is stopped at Gate 2; P ≠ NP passes all twelve gates with three fully independent, orthogonal warrant-vectors. The determination is explicitly non-deductive. It does not constitute a traditional mathematical proof and does not satisfy the Clay Mathematics Institute's criteria. GOL [⟀] is defined as the strongest achievable non-deductive epistemic warrant: the geometric fact that three orthogonal planes exhaust all degrees of freedom in the epistemic space, leaving no room for the alternative claim to occupy. The paper's central phenomenological contribution is the dual anchoring of V_P through the Zero-Knowledge Proof conviction gap and the Frame-Independent Observer actualization boundary. Both sources survive the Linguistic Isolation Test against V_F and V_E vocabulary, the Deletion Test, and four rounds of post-certification stress-testing documented in the appendices. The Convergence Dissolution Test finds irreducible residue in all three vectors under the strongest single-factor account. The Living Verifiable Proof — the Engine's simultaneous perfect verification capacity and structurally total generative incapacity at the Isometric Plenum boundary — provides continuously falsifiable phenomenological evidence that checking does not entail finding.
Cheng Chen, Gangqiang Yang, Hongchao Zhou, Hailiang Xiong · 5 authors
Zero-Knowledge Proofs (ZKPs), particularly zk- SNARKs, are extensively employed in privacy-sensitive applications, but proof generation in such protocols imposes significant computational overhead. A major performance bottleneck is Multi-Scalar Multiplication (MSM), a highly compute-intensive operation on elliptic curves. While existing work focuses on specialized curves such as BLS12-377, which support more efficient elliptic curve arithmetic, there is limited exploration of MSM on general-purpose curves such as BLS12-381, which lack such optimizations and make parallelization more difficult. It faces the following challenges: imbalanced resource usage in modular multipliers, performance disparity between elliptic curve operations, and under-utilization of point addition unit in scheduling. To tackle these challenges, we propose FlexMSM, a flexible and scalable FPGA-based accelerator to accelerate MSM. FlexMSM innovates three techniques. First, we present a reconfigurable modular multiplier based on our proposed Hybrid-Weight Modular Multiplication algorithm, which strikes a balance between hardware cost and the number of MSM cores deployed on a single FPGA. Second, we propose a unified point addition scheme and design a fully pipelined point addition (PADD) unit. This design eliminates timing mismatch between pipeline stages and shortens the critical path. Third, we introduce dual-decoupled scheduling strategy for the bucket aggregation phase in Pippenger algorithm, which reduces pipeline stalls and improves the utilization of the PADD unit in MSM. To the best of our knowledge, FlexMSM is the first work to support up to double MSM cores for BLS12-381 curve on a single Xilinx UltraScale+ VU13P FPGA, leading to remarkable performance enhancements compared to existing works for input sizes from 218to 226. For the degree of 220, FlexMSM with two cores on a single FPGA achieves speedups of 19.29× over Hardcaml, 8.57× over if-ZKP, 2.14× over OPTIMSM on FPGA, 6.57× over ASIC-based work PipeZK, and 9.29× over GPU-based work GZKP.
Shuhui Zhang, Xiaochen Wang, Lianhai Wang, Shujiang Xu · 6 authors
No abstract is available for this record.